Tongji Medical University

Psoriasis is a prevalent chronic disease affecting 2–3% of the global population. Cyclosporine A (CyA) has been widely used with great promise in the treatment of moderate to severe psoriasis despite various side effects associated with its systemic administration. Topical administration of CyA circumvents systemic side effects; however, the poor water solubility and large molecular weight of CyA pose challenges for dermal delivery. In this study, choline-based ionic liquids (ILs) were used to enhance the dermal delivery of CyA for the potential treatment of psoriasis. All four ILs tested significantly improved the solubility of CyA, which was greater than that of the control group with dimethyl sulfoxide (DMSO) as a solubilizer (20%, w/w). The saturated solubility of CyA in two of the ILs, choline geranate ([Ch][Ge]) and choline ricinoleate ([Ch][Ra]), reached more than 90 mg/mL, and the solubilization capability of the ILs except [Ch][Ci] was resistant to water dilution. The negligible change in CyA content determined by high-performance liquid chromatography and the secondary structure detected by circular dichroism spectroscopy confirmed the stability of CyA in the ILs. At 4 h in the in vitro penetration test, the amount of CyA retained in the skin in the IL groups was slightly greater than that in the control group (20% DMSO). The water content of the ILs significantly affected their penetration ability. When the water content increased from 10 to 70%, the dermal delivery of CyA first increased, peaked at a water content of 30%, and then decreased. The dermal delivery ability of [Ch][Ge] and [Ch][Ra] with a water content of 70% was still comparable to that of 20% DMSO. Moreover, CyA-loaded ILs (0.5%, w/w) significantly relieved the symptoms of psoriasis in an imiquimod (IMQ)-induced mouse model, and the levels of inflammatory factors, including tumor necrosis factor α, interleukin 22 and interleukin 17, in the affected area were reduced by 71.7%, 75.6%, and 89.3%, respectively. The IL tested, choline sorbate ([Ch][So]), showed low cytotoxicity to human immortalized epidermal cells (HaCaT). After 7 days of consecutive application, [Ch][So] did not cause significant irritation. In conclusion, ILs demonstrate promising potential for the dermal delivery of CyA for the treatment of psoriasis.

Gamma‐aminobutyric acid (GABA) B receptors (GABABRs) that acts slowly and maintains the inhibitory tone are versatile regulators in the complex nervous behaviors and their involvement in various neuropsychiatric disorders, such as anxiety, epilepsy, pain, drug addiction, and Alzheimer's disease. Additional study advances have implied the crucial roles of GABABRs in regulating feeding‐related behaviors, yet their therapeutic potential in addressing the neuropsychiatric disorders, binge eating, and feeding‐related disorders remains underutilized. This general review summarized the physiological structure and functions of GABABR, explored the regulation in various psychiatric disorders, feeding behaviors, binge eating, and metabolism disorders, and fully discussed the potential of targeting GABABRs and its regulator‐binding sites for the treatment of different psychiatric disorders, binge eating and even obesity. While agonists that directly bind to GABABR1 have some negative side effects, positive allosteric modulators (PAMs) that bind to GABABR2 demonstrate excellent therapeutic efficacy and tolerability and have better safety and therapeutic indexes. Moreover, phosphorylation sites of downstream GABABRs regulators may be novel therapeutic targets for psychiatric disorders, binge eating, and obesity. Further studies, clinical trials in particular, will be essential for confirming the therapeutic value of PAMs and other agents targeting the GABABR pathways in a clinical setting.

Facing the great challenge for efficient utilization of solar light, the design of photothermal‐propelled micromotors is significant for converting optical energy into thermal energy to achieve the in situ manipulated motion. Assisted by the photothermal‐propelled function, a synergistic photocatalytic‐photothermal antibacterial system is successfully constructed in this work, based on the Au‐CeO2 micromotor. The selective growth of CeO2 nanoparticles on the surface of Au nanorods (NRs) is achieved with the adjustable Au exposure ratio. The strong interaction of CeO2 with Au NRs realizes the enhanced visible light harvesting and the promoted photo‐induced charge separation. Especially, the self‐induced thermophoretic force on asymmetric lollipop‐like L‐Au‐CeO2 with higher Au exposure ratio is more powerful than that on symmetric core‐shelled CS‐Au‐CeO2 and dumbbell‐like D‐Au‐CeO2. As a result, its local temperature gradient is greater and thus realizes the in situ manipulated motion with higher velocity and stronger directionality. It further facilitates the contact with bacteria and promotes the synergistic photocatalytic‐photothermal antibacterial performance for the probe bacteria of Escherichia coli. This powerful photothermal‐propelled Au‐CeO2 micromotor shows significant potential for the microorganism control in biomedical and environmental applications.

In this editorial we comment on the article published in the recent issue of World Journal of Gastrointestinal Oncology . This study aims to explore the relationship between preoperative inflammation markers and the recurrence of gastrointestinal stromal tumors (GIST) after surgery. It is well known that the best-documented prognostic parameters for GIST are mitotic activity, tumor size and anatomical site. Besides, mutation status represents a prognostic as well as predictive factor. This study provides a new tool for postoperative recurrence risk assessment of GIST patients by establishing a line chart prediction model, which is certificated by previous research that high platelet-to-lymphocyte ratio and neutrophil-to-lymphocyte ratio correlated with increased tumour sizes, more advanced tumour stages and mitotic index. However, as a retrospective study, inevitable bias exists in the results; furthermore, the sample size of this study is relatively small, influencing the universality of the results. Moreover, when assessing risk rating and prognosis of GIST, some novel inflammatory makers could be taken into consideration, such as proenkephalin and SLITRK3. Overall, this study can offer an additional model for GIST prognosis and recurrence risk assessment, independent of the traditional prognostic factors of GIST.

Objective Kidney fibrosis is a key pathological feature in the progression of chronic kidney disease (CKD), traditionally diagnosed through invasive kidney biopsy. This study aimed to develop and validate a noninvasive, multi-center predictive model incorporating machine learning (ML) for assessing kidney fibrosis severity using biochemical markers. Methods This multi-center retrospective study included 598 patients with kidney fibrosis from four hospitals. A training cohort of 360 patients from Shanghai Tongji Hospital was used to develop a predictive nomogram and ML model, with fibrosis severity classified as mild or moderate-to-severe based on Banff scores. Logistic regression identified key predictors, which were incorporated into a nomogram and ML model. An external validation cohort of 238 patients from three additional hospitals was used for model evaluation. Results Serum creatinine (Scr), estimated glomerular filtration rate (eGFR), parathyroid hormone (PTH), brain natriuretic peptide (BNP), and sex were identified as independent predictors of kidney fibrosis severity. The nomogram demonstrated superior discriminative ability in the training cohort (AUC: 0.89, 95% CI: 0.85–0.92) compared to eGFR (AUC: 0.83, 95% CI: 0.78–0.87) and Scr (AUC: 0.87, 95% CI: 0.83–0.91). Among ML models, the Random Forest (RF) model achieved the highest AUC (0.98). In external validation, the nomogram and RF models maintained robust performance with AUCs of 0.86 and 0.79, respectively. Conclusion This study presents a validated, noninvasive, multi-center Scr-based machine learning model for assessing kidney fibrosis severity in CKD. The integration of a clinical nomogram and ML approach offers a novel, practical alternative to biopsy for dynamic fibrosis evaluation.

Micro/nanorobots are being increasingly utilized as new diagnostic and therapeutic platforms in the biomedical field, enabling remote navigation to hard‐to‐reach tissues and the execution of various medical procedures. Although significant progress has been made in the development of biomedical micro/nanorobots, how to achieve closed‐loop control of them from sensing, memory, and precise trajectory planning to feedback to carry out biomedical tasks remains a challenge. Bacteria with self‐propulsion and autonomous intelligence properties are well suited to be engineered as microrobots to achieve closed‐loop control for biomedical applications. By virtue of synthetic biology, bacterial microrobots possess an expanded genetic toolbox, allowing them to load input sensors to respond or remember external signals. To achieve accurate control in the complex physiological environment, the development of bacterial microrobots should be matched with the corresponding control system design. In this review, a detailed summary of the sensing and control mechanisms of bacterial microrobots is presented. The engineering and applications of bacterial microrobots in the biomedical field are highlighted. Their future directions of bacterial autonomous intelligent microrobots for precision medicine are forecasted.

Hepatocellular carcinoma (HCC), a severe consequence of hepatitis C virus infection, is significantly influenced by the virus’s non‐structural protein 3 (NS3). This study employed transcriptome sequencing to explore the role of NS3 in promoting HCC progression by comparing gene expression profiles between HCV‐infected HCC tissues and healthy liver controls. Key genes regulated by NS3 were identified and validated with quantitative reverse transcription PCR (RT‐qPCR) and western blot analyses. Functionality assays, including CCK‐8, BrdU, and Transwell migration and invasion tests, were performed to evaluate the effects of NS3 on HCC cell proliferation, migration, and invasion. Further investigation through a dual‐luciferase reporter and RNA pull‐down assays revealed that NS3 specifically upregulates circ_0001175. This circular RNA interacts with and inhibits miR‐130a‐5p, diminishing its regulatory impact on P53 by modulating the MDM4 pathway, thereby promoting oncogenic characteristics. The findings highlight the NS3‐induced circ_0001175/miR‐130a‐5p/MDM4/P53 pathway as a potential therapeutic target, offering promising directions for treatment strategies in HCV‐related HCC.

OBJECTIVES Reliable methods for predicting pathological complete response (pCR) in non-small cell lung cancer (NSCLC) patients undergoing neoadjuvant chemoimmunotherapy are still under exploration. Although Fluorine-18 fluorodeoxyglucose-positron emission tomography/computed tomography (18F-FDG PET/CT) features reflect tumour response, their utility in predicting pCR remains controversial. METHODS This retrospective analysis included NSCLC patients who received neoadjuvant chemoimmunotherapy followed by 18F-FDG PET/CT imaging at Shanghai Pulmonary Hospital from October 2019 to August 2024. Eligible patients were randomly divided into training and validation cohort at a 7:3 ratio. Relevant 18F-FDG PET/CT features were evaluated as individual predictors and incorporated into five machine learning (ML) models. Model performance was assessed using the area under the receiver operating characteristic curve (AUC), and Shapley additive explanation (SHAP) was applied for model interpretation. RESULTS A total of 205 patients were included, with 91 (44.4%) achieving pCR. Post-treatment tumour maximum standardized uptake value (SUVmax) demonstrated the highest predictive performance among individual predictors, achieving an AUC of 0.72 (95% CI: 0.65—0.79), while ΔT SUVmax achieved an AUC of 0.65 (95% CI: 0.53—0.77). The Light Gradient Boosting Machine (LightGBM) algorithm outperformed other models and individual predictors, achieving an average AUC of 0.87 (95% CI: 0.78—0.97) in training cohort and 0.83 (95% CI: 0.72—0.94) in validation cohort. SHAP analysis identified post-treatment tumour SUVmax and post-treatment nodal volume as key contributors. CONCLUSIONS This ML models offer a non-invasive and effective approach for predicting pCR after neoadjuvant chemoimmunotherapy in NSCLC.

Aim Non‐suicidal self‐injury (NSSI) is a prevalent behavior that is associated with various mental disorders characterized by self‐injury without suicidal intent. However, both the neurobiological bases and indicators of suicidal risk remain elusive, impeding the intervention of this disorder. NSSI is regulated by the reward system, which also regulates time perception. This study aimed to investigate time perception characteristics in NSSI patients and to evaluate their potential for identifying suicidal thoughts and behaviors (STBs). Methods A cohort study was conducted, which involved 93 NSSI and psychiatric disorders comorbidity (NPC) patients and 84 healthy controls. Participants completed psychological scales and temporal reproduction tasks to determine the characteristics of time perception in adolescents with NPC. Follow‐up assessments were conducted 3 months later to evaluate the emergence of STBs. Logistic regression and nomograms were utilized to explore the predictive value of time perception characteristics on STBs. Results Adolescents with NPC demonstrated significant characteristics in time perception, with a lower reproduction ratio (DRR) and higher coefficient of variation (CV). Notably, lower CV at baseline was associated with a higher probability of STBs during follow‐up. The study revealed that time perception effectively predicts the risk of subsequent STBs in NPC patients. Conclusion This study identifies characteristics of time perception in adolescent NPC patients, which may serve as a novel behavioral indicator for the early identification of risk for suicide. The findings contribute to a better understanding of the neurobiological bases of NSSI and highlight the potential of time perception tasks in the early identification of adverse outcomes, offering novel insights for intervention strategies.

This study aims to develop a short-term spatiotemporal CT radiomics model to predict the major pathological response (MPR) to neoadjuvant chemoimmunotherapy (NCI) in NSCLC by decoding the intra- and peri-tumoral imaging phenotypes. A total of 352 patients undergoing curative surgery following NCI for NSCLC were enrolled from two centers, forming a training cohort (n = 186), an internal validation cohort (n = 80), and an external validation cohort (n = 86). Intra- and peri-tumoral CT radiomics features were computed to capture imaging phenotypes of the tumor microenvironment. Delta radiomics features were also calculated by quantifying changes in each radiomics feature. A support vector machine classifier was utilized to develop the short-term spatiotemporal model by analyzing changes in radiomics features. The multi-timepoint short-term spatiotemporal model, incorporating pre-treatment, post-treatment and delta radiomic features, achieved AUC values of 0.84, 0.77, and 0.75 in the training, internal validation, and external validation cohorts, respectively. These results significantly outperformed the RECIST model and pre-treatment model, with p-values < 0.05 indicating statistical significance. This study demonstrates that short-term temporal analysis of intra- and peri-tumoral CT radiomics is a promising approach for predicting MPR to NCI in NSCLC. These findings underscore the potential of radiomics as a non-invasive tool for assessing treatment response and guiding personalized therapy in NSCLC patients. Question Neoadjuvant chemoimmunotherapy has improved in major pathological response rate for non-small cell lung cancer (NSCLC), but it is unclear which patients will benefit most. Findings The multi-timepoint short-term spatiotemporal model based on CT pictures demonstrates high predictive performance for assessing major pathological response following neoadjuvant chemoimmunotherapy in NSCLC. Clinical relevance Short-term intra- and peri-tumoral CT radiomics is a promising approach for predicting major pathological response to neoadjuvant chemoimmunotherapy in NSCLC. These findings underscore the potential of radiomics as a non-invasive tool for assessing treatment response in NSCLC.

Objectives Cerebral infarction is an acute ischemic cerebrovascular disease; elderly patients with cerebral infarction often have frailty syndrome. Therefore, the aim of this study was to analyze the risk factors and their diagnostic value of frailty in elderly patients with cerebral infarction. Methods In this retrospective cohort study, the medical records (from October 2017 to September 2020) of patients with cerebral infarction (n=395) were analyzed. According to different frailty statuses, patients were divided into the health group (n=166) and the prefrailty group (n=229). The diagnostic value of various parameters for the occurrence of pre-frailty was assessed by the receiver operating characteristic (ROC) curve and area under the ROC curve (AUC). The risk factors were analyzed by single-factor and multi-factor analyses. Results Interleukin-6 (IL-6, P <0.001), C-reactive protein (CRP), prealbumin (PA, P <0.001), albumin (ALB, P <0.001), and brain natriuretic peptide (BNP, P <0.001) had higher diagnostic value for the occurrence of prefrailty in elderly patients with cerebral infarction. Single-factor and multi-factor analysis results revealed that the length of stay (LOS), comorbidity with nervous system diseases, high Charlson comorbidity index (CCI), high National Institute of Health stroke scale score, IL-6, BNP, ALB, PA, and creatine kinase might risk the factors for prefrailty occurrence ( P <0.05). After the elimination of interference factors, LOS, high CCI, IL-6, and ALB were confirmed to be key risk factors for the occurrence of prefrailty ( P <0.05). Conclusion LOS, high CCI, IL-6, and ALB are the underlying risk factors for the occurrence of prefrailty in elderly patients with cerebral infarction, which provides a theoretical basis for clinical disease diagnosis.

Background The anti‐inflammatory cytokine interleukin‐4 (IL4) has been recognised as a protective factor in various cardiovascular events, yet its prognostic value in patients with pulmonary hypertension (PH) remains unclear. The study aimed to measure the levels of plasma IL4 in patients with PH and to explore their potential association with disease risk and outcomes. Methods In this observational study, we analysed the levels of plasma IL4 in 766 PH patients and 191 healthy controls in Shanghai Pulmonary Hospital from October 2009 to January 2024. To establish the correlations between plasma IL4 levels and the risk and outcomes of PH, all patients were followed up from June 2013 to June 2024. The Spearman correlation test was employed to evaluate the relationships between IL4 and right heart catheterisation parameters among patients with PH. Receiver operating characteristic (ROC) curves were generated to evaluate the diagnostic performance of IL4 for PH. The Cox proportional hazards models and Kaplan–Meier survival curves were used to assess the prognostic value of IL4 levels. Logistic regression analysis was performed to predict PH incidence. A nomogram was constructed to predict mortality, and its clinical utility was validated using decision curve analysis (DCA). Results Plasma IL4 levels were significantly decreased in patients with PH compared with controls ( p < 0.001), as well as in different PH groups ( p < 0.05 for all). The logistic regression analyses indicated that the lower IL4 levels were associated with the high risk of PH (OR = 0.79, 95% CI: 0.716–0.872; p < 0.001). IL4 levels correlated inversely with NT‐proBNP ( r = −0.10, p < 0.05) and mPAP ( r = −0.01, p < 0.05), and positively with CI ( r = 0.12, p < 0.05) and PaSaO2 ( r = 0.11, p < 0.05), indicating an association with disease severity. Kaplan–Meier analysis revealed that patients with IL4 ≥ 2.8774 pg/mL had a 3‐year cumulative survival rate of 91.28%, compared with 82.83% for those with IL4 < 2.8774 pg/mL (log–rank p = 0.007). Cox regression confirmed IL4 as an independent predictor of survival (HR = 0.810, 95% CI: 0.660–0.993; p = 0.043). A diagnostic model combining IL4, 6MWD and NT‐proBNP demonstrated good prognostic value (AUC = 0.692, p < 0.0001). Conclusions Plasma IL4 levels were significantly decreased in patients with PH, exhibiting a negative correlation with disease severity; furthermore, lower IL4 levels may serve as a prognostic indicator of poor outcomes in patients with PH.

Particulate matter with aerodynamic diameter ≤ 2.5 μm (PM 2.5 ) at high concentrations in dental clinics poses significant health risks to healthcare professionals. However, the morphology and chemical composition of PM 2.5 in specific environments are not yet fully elucidated. In this study, we investigated the concentration, morphology, chemical composition, and health assessment of PM 2.5 collected in a multi‐chair dental clinic in Shanghai, China. Scanning electron microscopy (SEM) and energy‐dispersive X‐ray spectroscopy (EDS) were performed to observe the morphology and elemental composition of indoor and outdoor PM 2.5 . Chemicals were measured for their concentrations using X‐ray fluorescence spectrometry (XRF). In the dental clinic, the indoor PM 2.5 concentration ranged from 2.01 to 114.59 μg/m ³ , with a mean of 23.31 μg/m ³ , while the outdoor PM 2.5 concentration ranged from 2.88 to 157.4 μg/m ³ , with a mean of 30.98 μg/m ³ . Indoor particles showed more rough, irregular mineralization, which was confirmed as the dominant elements of Ca, P, Si, and zirconia (Zr) by EDS. The average concentrations of Ca, P, Cu, Sr, and Sb indoors were lower than those outdoors ( p < 0.05). We also found that Cd, As, and Ni exceeded the annual limits of the Ambient Air Quality Standards of WHO. For the health assessment, the carcinogenic risks of Cd, As, and Cr were higher than the minimum acceptable level (1 × 10 ⁻⁶ ), with values of 3.68 × 10 ⁻⁵ , 1.10 × 10, ⁻⁵ and 5.52 × 10 ⁻⁶ , respectively, and the non‐carcinogenic risk of Cd was the highest, as illustrated by the Hazard Quotient of 2.04. These findings indicate that dental healthcare professionals may be exposed to PM 2.5 containing high concentrations of toxic metals and carcinogenic elements over the long term. This study highlights the importance of protective measures (e.g., the adoption of efficient air purification systems) to minimize the risk of particle inhalation for both patients and professionals.

Circadian clocks have a fundamental role in many physiological processes. Bmal1 (basic helix–loop–helix ARNT like 1) is a central master circadian clock gene. The global Bmal1 knockout mice were shown to have a loss of circadian rhythms, acceleration of aging, and shortened life span. However, global Bmal1 knockout mice did not exactly reflect the Bmal1 function in specific cell or tissue types. To address the importance of circadian rhythms in macrophages, we generated myeloid‐specific Bmal1 knockout mice. The efficacy of Bmal1 gene deletion in macrophages was identified at DNA, transcription, protein levels, and function. In contrast to global Bmal1 knockout mice, Bmal1 flox/flox and Bmal1 mye−/− mice did not exhibit aging phenotypes. However, the deletion of Bmal1 resulted in a loss of rhythmic expression of the circadian genes in macrophages. RNA‐Seq revealed that Bmal1 regulated the expression of cell death‐related genes in macrophages. Furthermore, these genes have been identified as clock‐controlled genes in rhythmic cell models, and Bmal1 controlled the rhythmic expression of these genes in macrophages. Finally, Bmal1 inhibited RSL3‐induced ferroptosis in macrophages through Phgdh. In summary, the model of myeloid‐specific Bmal1 knockout mice was successfully constructed, providing a tool for the study of the roles of Bmal1 in macrophages and the peripheral circadian clock. Meanwhile, Bmal1 regulates ferroptosis in macrophages.

Focal cortical dysplasia type II (FCDII) is a major cause of drug-resistant epilepsy, but genetic factors explain only some cases, suggesting other mechanisms. In this study, we conduct a molecular analysis of brain lesions and adjacent areas in FCDIIb patients. By analyzing over 217,506 single-nucleus transcriptional profiles from 15 individuals, we find significant changes in smooth muscle cells (SMCs) and astrocytes. We identify abnormal vascular malformations and a unique type of SMC that we call “Firework cells”, which migrate from blood vessels into the brain parenchyma and associate with VIM⁺ cells. These abnormalities create localized ischemic-hypoxic (I/H) microenvironments, as confirmed by clinical data, further impairing astrocyte function, activating the HIF-1α/mTOR/S6 pathway, and causing neuronal loss. Using zebrafish models, we demonstrate that vascular abnormalities resulting in I/H environments promote seizures. Our results highlight vascular malformations as a factor in FCDIIb pathogenesis, suggesting potential therapeutic avenues.

Background Graves disease (GD) is an autoimmune thyroid disorder characterized by hyperthyroidism and autoantibodies. The COVID-19 pandemic has raised questions about its potential relationship with autoimmune diseases like GD. Objective This study aims to investigate the causal association between COVID-19 and GD through Mendelian randomization (MR) analysis and assess the impact of COVID-19 on GD. Methods We conducted an MR study using extensive genome-wide association study data for GD and COVID-19 susceptibility and its severity. We used stringent single nucleotide polymorphism selection criteria and various MR methodologies, including inverse-variance weighting, MR-Egger, and weighted median analyses, to assess causal relationships. We also conducted tests for directional pleiotropy and heterogeneity, as well as sensitivity analyses. Results The MR analysis, based on the largest available dataset to date, did not provide evidence supporting a causal relationship between COVID-19 susceptibility (odds ratio [OR] 0.989, 95% CI 0.405‐2.851; P =.93), COVID-19 hospitalization (OR 0.974, 95% CI 0.852‐1.113; P =.70), COVID-19 severity (OR 0.979, 95% CI 0.890‐1.077; P =.66), and GD. Tests for directional pleiotropy and heterogeneity, as well as sensitivity analyses, supported these findings. Conclusions This comprehensive MR study does not provide sufficient evidence to support a causal relationship between COVID-19 and the onset or exacerbation of GD. These results contribute to a better understanding of the potential association between COVID-19 and autoimmune diseases, alleviating concerns about a surge in autoimmune thyroid diseases due to the pandemic. Further research is warranted to explore this complex relationship thoroughly.